Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A computer-implemented method for generating a scaled reconstruction of an object relative to an individual's anatomy, using a computer system, the method comprising: receiving, from an image capture device, a first digital input comprising a digital representation of a calibration target and an object and/or individual's anatomy proximate to the calibration target; defining a three-dimensional coordinate system representing a three-dimensional space for scaling the object using the calibration target; positioning the object in the three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; aligning the object to the calibration target in the three-dimensional coordinate system based on the first digital input; generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system based on the first digital input; receiving, from a depth sensor, a second digital input comprising depth information of the object and/or the individual's anatomy; and generating a digital representation of the scaled reconstruction of the object overlaid on the individual's anatomy based on the first digital input and the second digital input comprising the depth information of the object and/or the individual's anatomy based on the second digital input received from the depth sensor.
This invention relates to a computer-implemented method for generating a scaled reconstruction of an object relative to an individual's anatomy. The method addresses the challenge of accurately positioning and scaling digital representations of objects in three-dimensional space, particularly when integrating them with anatomical features of a person. The process begins by capturing a digital representation of a calibration target alongside an object or individual's anatomy using an image capture device. A three-dimensional coordinate system is then defined to establish a spatial reference for scaling the object. The object and calibration target are positioned within this coordinate system, and the object is aligned to the calibration target based on the captured digital input. A scaled reconstruction of the object is generated from this alignment. Additionally, depth information of the object or anatomy is obtained from a depth sensor, enabling the creation of a digital representation where the scaled object is overlaid onto the individual's anatomy. This method ensures precise scaling and positioning of digital objects in relation to anatomical features, facilitating applications in medical imaging, augmented reality, and other fields requiring accurate spatial integration of digital and physical elements.
2. The method of claim 1 , further comprising: determining three-dimensional measurements of the calibration target in the three-dimensional coordinate system; and further generating the scaled reconstruction of the object based on the three-dimensional measurements of the calibration target.
This invention relates to three-dimensional (3D) reconstruction systems, specifically improving the accuracy of 3D measurements by incorporating a calibration target. The problem addressed is the inherent inaccuracies in 3D reconstruction due to sensor distortions, environmental factors, or misalignment, which can lead to distorted or improperly scaled 3D models. The method involves capturing multiple images of an object from different perspectives using one or more imaging devices. These images are processed to generate a preliminary 3D reconstruction of the object. To enhance accuracy, a calibration target with known dimensions is placed within the imaging field. The system determines precise 3D measurements of this calibration target in a 3D coordinate system, accounting for its position, orientation, and scale. These measurements are then used to scale and refine the preliminary 3D reconstruction, ensuring the final model is accurately proportioned and free from distortion. The calibration target may include features such as markers, patterns, or geometric shapes that facilitate precise measurement. This approach improves the reliability of 3D reconstruction by providing a reference for scaling and alignment, making it particularly useful in applications requiring high precision, such as industrial inspection, medical imaging, or metrology. The method ensures that the final 3D model is dimensionally accurate and consistent with real-world measurements.
3. The method of claim 1 , wherein the calibration target is comprised of a parameterized three-dimensional reconstruction.
A method for calibrating a three-dimensional imaging system involves using a calibration target that is generated as a parameterized three-dimensional reconstruction. The calibration target is designed to facilitate accurate alignment and measurement of the imaging system's performance. The parameterized reconstruction allows for precise adjustments to the target's geometry, enabling the system to account for variations in imaging conditions, such as perspective distortion or depth perception errors. This approach improves the accuracy of the calibration process by providing a flexible and adaptable reference model. The method ensures that the imaging system can reliably capture and process three-dimensional data, which is critical for applications requiring high precision, such as medical imaging, industrial inspection, or autonomous navigation. The use of a parameterized target allows for dynamic adjustments during calibration, enhancing the system's ability to compensate for environmental factors and sensor limitations. This technique ensures that the imaging system maintains consistent performance across different operating conditions.
4. The method of claim 1 , further comprising: receiving a three-dimensional reconstruction of the object; aligning the calibration target to the three-dimensional reconstruction of the object; and generating the scaled reconstruction based on the alignment of the calibration target to the three-dimensional reconstruction of the object.
This invention relates to three-dimensional (3D) reconstruction and calibration techniques, particularly for improving the accuracy of 3D models by aligning a calibration target with the reconstructed object. The problem addressed is the lack of precise scaling and alignment in 3D reconstructions, which can lead to inaccuracies in measurements and applications requiring high precision. The method involves receiving a 3D reconstruction of an object, which may be generated using techniques such as photogrammetry, laser scanning, or structured light. A calibration target, which is a reference object with known dimensions and features, is then aligned to the 3D reconstruction. This alignment process ensures that the calibration target is accurately positioned relative to the reconstructed object. Based on this alignment, a scaled reconstruction is generated, where the dimensions of the reconstructed object are adjusted to match the known dimensions of the calibration target. This scaling corrects any distortions or inaccuracies in the original reconstruction, resulting in a more precise 3D model. The calibration target may include features such as markers, grids, or geometric patterns that facilitate alignment. The alignment process may involve computational techniques such as feature matching, registration, or optimization algorithms to ensure accurate positioning. The scaled reconstruction can then be used in applications requiring high precision, such as metrology, quality control, or reverse engineering. This method improves the reliability and accuracy of 3D reconstructions by leveraging known reference dimensions from the calibration target.
5. The method of claim 4 , further comprising: generating the three-dimensional reconstruction of the object.
Technical Summary: This invention relates to three-dimensional (3D) reconstruction of objects, addressing the challenge of accurately capturing and reconstructing the spatial structure of physical objects from sensor data. The method involves processing sensor data, such as images or point clouds, to generate a detailed 3D model of the object. The reconstruction process includes aligning and merging multiple sensor measurements to form a coherent 3D representation, ensuring accuracy and completeness. The method may incorporate techniques such as feature matching, surface interpolation, or volumetric modeling to refine the reconstruction. Additionally, the system may use calibration data to correct distortions or errors in the sensor measurements, improving the fidelity of the final 3D model. The invention is applicable in fields like computer vision, robotics, and manufacturing, where precise 3D object modeling is essential for tasks such as object recognition, simulation, or quality control. The method ensures that the reconstructed 3D model accurately reflects the object's geometry, enabling reliable downstream applications.
6. The method of claim 1 , further comprising: determining, from the first digital input, an image including the calibration target and the object and/or the individual's anatomy; determining, from the image, a three-dimensional location of the calibration target and a three-dimensional location of the object; and positioning the calibration target in the three-dimensional coordinate system and positioning the object in the three-dimensional coordinate system, based on the three-dimensional location of the calibration target and the three-dimensional location of the object.
This invention relates to a method for calibrating and positioning objects or anatomical features in a three-dimensional coordinate system using digital imaging. The method addresses the challenge of accurately aligning physical objects or anatomical structures within a defined spatial framework, which is critical in applications such as medical imaging, robotics, and augmented reality. The method involves capturing a digital image that includes a calibration target and either an object or an individual's anatomy. From this image, the system determines the three-dimensional locations of both the calibration target and the object or anatomical feature. The calibration target serves as a reference point within the coordinate system, allowing precise spatial mapping. By analyzing the image, the system calculates the exact positions of the target and the object in three-dimensional space. These positions are then used to position both the calibration target and the object within the coordinate system, ensuring accurate alignment and registration. This process enables precise tracking, measurement, and interaction with physical or anatomical structures in applications requiring high spatial accuracy.
7. The method of claim 1 , further comprising: determining a scaling measurement based on aligning the object to the calibration target in the three-dimensional coordinate system; and generating the scaled reconstruction of the object based on the scaling measurement.
This invention relates to three-dimensional (3D) object reconstruction, specifically addressing the challenge of accurately scaling and aligning 3D reconstructions of objects relative to a known calibration target. The method involves capturing multiple images of an object from different perspectives and processing these images to generate a 3D reconstruction. The key improvement lies in determining a scaling measurement by aligning the reconstructed object with a calibration target within a 3D coordinate system. This alignment ensures the reconstruction is accurately scaled to real-world dimensions. The scaled reconstruction is then generated based on this measurement, providing a precise and dimensionally accurate 3D model of the object. The calibration target serves as a reference, enabling consistent scaling across different reconstructions. This approach enhances the reliability of 3D reconstructions for applications such as manufacturing, quality control, and digital archiving, where accurate dimensional fidelity is critical. The method ensures that the reconstructed object matches the physical dimensions of the real-world object, overcoming limitations in traditional reconstruction techniques that may produce models with incorrect scaling.
8. The method of claim 1 , wherein the first digital input includes one or more of a series of images from a singular image sensor taken from different camera positions, a video taken from different camera positions, a series of images or a video taken from different perspectives with depth information included, a 3D point cloud captured from a depth or 3D sensor, a series of images from multiple 2D sensors, a video captured from multiple 2D sensors, or a combination thereof.
This invention relates to digital input methods for generating three-dimensional (3D) models or representations. The problem addressed is the need for versatile and accurate input data sources to create detailed 3D reconstructions from various types of digital inputs. The invention provides a method that processes different forms of digital input to generate 3D models, ensuring compatibility with diverse data sources. The method accepts a first digital input, which may include one or more of the following: a series of images captured by a single image sensor from different camera positions, a video recorded from varying camera positions, a series of images or a video with depth information from different perspectives, a 3D point cloud from a depth or 3D sensor, a series of images from multiple 2D sensors, a video captured by multiple 2D sensors, or a combination of these inputs. This flexibility allows the method to work with various imaging techniques, including traditional 2D cameras, depth sensors, and multi-camera setups, enabling robust 3D reconstruction across different scenarios. The approach ensures that the input data, regardless of its source or format, can be effectively processed to generate accurate 3D models.
9. A system for generating a scaled reconstruction of an object relative to an individual's anatomy, the system comprising: a data storage device storing instructions for generating a scaled reconstruction for a consumer product; and a processor configured to execute the instructions to perform a method including: receiving, from an image capture device, a first digital input comprising a digital representation of a calibration target and an object and/or individual's anatomy proximate to the calibration target; defining a three-dimensional coordinate system representing a three-dimensional space for scaling the object using the calibration target; positioning the object in the three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; aligning the object to the calibration target in the three-dimensional coordinate system based on the first digital input; generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system based on the first digital input; receiving, from a depth sensor, a second digital input comprising depth information of the object and/or the individual's anatomy; and generating a digital representation of the scaled reconstruction of the object overlaid on the individual's anatomy based on the first digital input and the second digital input comprising the depth information of the object and/or the individual's anatomy based on the second digital input received from the depth sensor.
This system enables the generation of a scaled reconstruction of an object relative to an individual's anatomy using digital imaging and depth sensing. The system addresses the challenge of accurately visualizing how an object, such as a consumer product, would appear when placed in proximity to a person's body, ensuring proper scaling and alignment. The system includes a data storage device containing instructions for generating scaled reconstructions and a processor that executes these instructions. The processor receives a first digital input from an image capture device, which includes a digital representation of a calibration target and either an object or an individual's anatomy near the calibration target. A three-dimensional coordinate system is defined to scale the object using the calibration target. The object and calibration target are positioned within this coordinate system, and the object is aligned to the calibration target based on the first digital input. A scaled reconstruction of the object is then generated based on this alignment. Additionally, the system receives a second digital input from a depth sensor, which provides depth information of the object or the individual's anatomy. This depth information is used to generate a digital representation of the scaled reconstruction of the object overlaid on the individual's anatomy, combining both the first and second digital inputs for an accurate visualization. The system ensures precise scaling and positioning of the object relative to the individual's anatomy, enhancing the accuracy of virtual try-on or product placement applications.
10. The system of claim 9 , wherein the system is further configured for: determining three-dimensional measurements of the calibration target in the three-dimensional coordinate system; and further generating the scaled reconstruction of the object based on the three-dimensional measurements of the calibration target.
This invention relates to a system for generating a scaled three-dimensional reconstruction of an object using a calibration target. The system addresses the challenge of accurately determining the real-world scale of three-dimensional reconstructions obtained from imaging data, which is critical for applications such as metrology, quality control, and augmented reality. The system includes a calibration target with known dimensions, which is placed within the field of view of one or more imaging devices. The system captures images or other sensor data of the calibration target and the object to be reconstructed. It then processes this data to determine the three-dimensional measurements of the calibration target within a three-dimensional coordinate system. Using these measurements, the system scales the three-dimensional reconstruction of the object to match the known dimensions of the calibration target, ensuring accurate real-world scaling. The system may also include components for capturing the imaging data, such as cameras or depth sensors, and processing units for analyzing the data to generate the three-dimensional reconstruction. The calibration target may be a physical object with predefined geometric features, such as markers or patterns, that facilitate precise measurement. The system's ability to scale the reconstruction based on the calibration target's known dimensions improves the accuracy and reliability of three-dimensional measurements in various applications.
11. The system of claim 9 , wherein the calibration target is comprised of a parameterized three-dimensional reconstruction.
A system for calibrating imaging devices uses a parameterized three-dimensional reconstruction as a calibration target. The calibration target is a 3D model that can be adjusted based on specific parameters, allowing for precise alignment and calibration of imaging systems. This approach improves accuracy by providing a flexible, configurable reference that adapts to different calibration scenarios. The system may include a processor that processes image data from the imaging device and compares it to the 3D reconstruction to determine calibration parameters. The calibration target can be modified in real-time to account for variations in imaging conditions, such as lighting or perspective. This method ensures consistent and reliable calibration across different environments and imaging setups. The use of a parameterized 3D model allows for dynamic adjustments, enhancing the system's adaptability and performance. The calibration process may involve iterative refinement, where the 3D reconstruction is updated based on feedback from the imaging device to achieve optimal alignment. This system is particularly useful in applications requiring high-precision imaging, such as medical imaging, industrial inspection, or augmented reality. The parameterized 3D reconstruction enables precise calibration without the need for physical targets, reducing setup time and improving efficiency.
12. The system of claim 11 , wherein the system is further configured for: receiving a three-dimensional reconstruction of the object; aligning the calibration target to the three-dimensional reconstruction of the object; and generating the scaled reconstruction based on the alignment of the calibration target to the three-dimensional reconstruction of the object.
This invention relates to a system for generating a scaled three-dimensional reconstruction of an object using a calibration target. The system addresses the challenge of accurately scaling and aligning three-dimensional reconstructions of objects, which is critical for applications such as metrology, quality control, and reverse engineering. The system receives a three-dimensional reconstruction of the object, which may be obtained through methods such as photogrammetry, laser scanning, or structured light scanning. The system then aligns a calibration target to the three-dimensional reconstruction. The calibration target provides known reference dimensions, enabling precise scaling of the reconstruction. By aligning the calibration target to the reconstruction, the system generates a scaled version of the three-dimensional model, ensuring accurate dimensional fidelity. This process compensates for distortions or inaccuracies in the original reconstruction, resulting in a high-precision scaled model. The system may also include features for capturing images of the object and the calibration target, processing the images to generate the three-dimensional reconstruction, and refining the alignment and scaling based on additional calibration data. The invention improves the accuracy and reliability of three-dimensional measurements, making it suitable for industrial and scientific applications requiring precise dimensional analysis.
13. The system of claim 12 , wherein the system is further configured for: generating the three-dimensional reconstruction of the object.
Technical Summary: This invention relates to a system for generating three-dimensional reconstructions of objects, addressing the challenge of accurately capturing and reconstructing physical objects in a digital format. The system is designed to process input data, such as images or sensor measurements, to create a detailed three-dimensional model of the object. This involves computational techniques to analyze spatial relationships, surface geometry, and other relevant features of the object. The system may incorporate algorithms for data fusion, noise reduction, and geometric alignment to ensure high-fidelity reconstructions. Additionally, the system may include modules for optimizing the reconstruction process, such as adjusting parameters based on the input data quality or object complexity. The generated three-dimensional model can be used for applications in fields like manufacturing, medical imaging, or virtual reality, where precise digital representations of physical objects are required. The system's ability to produce accurate reconstructions enhances its utility in scenarios demanding high precision and reliability.
14. The system of claim 9 , wherein the system is further configured for: determining, from the first digital input, an image including the calibration target and the object and/or the individual's anatomy; determining, from the image, a three-dimensional location of the calibration target and a three-dimensional location of the object; and positioning the calibration target in the three-dimensional coordinate system and positioning the object in the three-dimensional coordinate system, based on the three-dimensional location of the calibration target and the three-dimensional location of the object.
This invention relates to a medical imaging system that integrates calibration targets with patient anatomy and medical objects to improve spatial accuracy in three-dimensional coordinate systems. The system addresses the challenge of precisely aligning medical instruments, implants, or anatomical features within a defined coordinate space, which is critical for procedures like surgery, radiation therapy, or diagnostic imaging. The system captures a digital input, such as an image or scan, containing a calibration target and either an object (e.g., a surgical tool or implant) or a patient's anatomy. From this input, the system identifies the calibration target and the object/anatomy, then determines their respective three-dimensional locations. Using these locations, the system positions both the calibration target and the object/anatomy within a shared three-dimensional coordinate system. This ensures accurate spatial registration, enabling precise navigation and interaction between medical tools and patient anatomy. The calibration target serves as a reference point, allowing the system to map the object or anatomy relative to it. This process enhances procedural accuracy by reducing errors in positioning and alignment, which is particularly valuable in minimally invasive surgeries or radiation treatments where precision is critical. The system may also include additional features, such as real-time tracking or adaptive adjustments, to maintain accuracy during dynamic procedures.
15. The system of claim 9 , wherein the system is further configured for: determining a scaling measurement based on aligning the object to the calibration target in the three-dimensional coordinate system; and generating the scaled reconstruction of the object based on the scaling measurement.
This invention relates to a system for generating a scaled three-dimensional reconstruction of an object using a calibration target. The system addresses the challenge of accurately determining the size and dimensions of an object in a three-dimensional space, which is critical for applications such as metrology, quality control, and augmented reality. The system includes a calibration target with known dimensions, which serves as a reference for scaling measurements. The system captures images or data of the object and the calibration target, then processes this data to align the object with the calibration target within a three-dimensional coordinate system. By analyzing this alignment, the system calculates a scaling measurement that accurately represents the object's dimensions relative to the known dimensions of the calibration target. Using this scaling measurement, the system generates a scaled reconstruction of the object, ensuring precise dimensional accuracy. The system may also include components for capturing the object's data, such as cameras or sensors, and processing units for performing the alignment and scaling calculations. This approach improves the reliability and accuracy of three-dimensional reconstructions, making it suitable for applications requiring precise measurements.
16. The system of claim 9 , wherein the first digital input includes one or more of a series of images from a singular image sensor taken from different camera positions, a video taken from different camera positions, a series of images or a video taken from different perspectives with depth information included, a 3D point cloud captured from a depth or 3D sensor, a series of images from multiple 2D sensors, a video captured from multiple 2D sensors, or a combination thereof.
This invention relates to a system for capturing and processing digital input data to generate a three-dimensional (3D) representation of an environment. The system addresses the challenge of accurately reconstructing 3D models from various types of input data, which may include images, videos, or depth information captured from different perspectives or positions. The system processes a first digital input, which can be one or more of the following: a series of images from a single image sensor taken at different camera positions, a video captured from different camera positions, a series of images or a video with depth information included, a 3D point cloud from a depth or 3D sensor, a series of images from multiple 2D sensors, a video captured from multiple 2D sensors, or a combination of these inputs. The system integrates these diverse data sources to reconstruct a coherent 3D model, enabling applications in fields such as augmented reality, robotics, and 3D mapping. The flexibility in input types allows the system to adapt to different capture scenarios, improving accuracy and usability in real-world environments.
17. A non-transitory computer readable medium for use on a computer system containing computer-executable programming instructions for generating a scaled reconstruction of an object relative to an individual's anatomy, the method comprising: receiving, from an image capture device, a first digital input comprising a digital representation of a calibration target and an object and/or individual's anatomy proximate to the calibration target; defining a three-dimensional coordinate system representing a three-dimensional space for scaling the object using the calibration target; positioning the object in the three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; aligning the object to the calibration target in the three-dimensional coordinate system based on the first digital input; generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system based on the first digital input; receiving, from a depth sensor, a second digital input comprising depth information of the object and/or the individual's anatomy; and generating a digital representation of the scaled reconstruction of the object overlaid on the individual's anatomy based on the first digital input and the second digital input comprising the depth information of the object and/or the individual's anatomy based on the second digital input received from the depth sensor.
This invention relates to digital reconstruction and scaling of objects relative to human anatomy using calibration targets and depth sensing. The system captures a digital representation of an object and/or an individual's anatomy alongside a calibration target, which serves as a reference for scaling. A three-dimensional coordinate system is defined to position and align the object and calibration target accurately. The system then generates a scaled reconstruction of the object by comparing its position to the calibration target within this coordinate system. Additionally, depth information from a depth sensor is integrated to refine the reconstruction. The final output is a digital representation of the scaled object overlaid on the individual's anatomy, combining the initial digital input with depth data for precise spatial alignment. This technology enables accurate scaling and positioning of objects in relation to human anatomy, useful in applications such as medical imaging, augmented reality, or virtual try-on systems. The system automates the scaling process by leveraging calibration targets and depth sensing, ensuring consistency and precision in the reconstruction.
18. The non-transitory computer readable medium of claim 17 , the method further comprising: determining three-dimensional measurements of the calibration target in the three-dimensional coordinate system; and further generating the scaled reconstruction of the object based on the three-dimensional measurements of the calibration target.
This invention relates to three-dimensional (3D) reconstruction systems, specifically improving the accuracy of 3D reconstructions by incorporating calibration targets. The problem addressed is the inherent inaccuracies in 3D measurements due to sensor distortions, misalignments, or scaling errors, which can lead to distorted or improperly sized reconstructions. The system includes a method for generating a scaled 3D reconstruction of an object using a calibration target with known dimensions. The method involves capturing multiple images or sensor data of the object and the calibration target from different viewpoints. The system processes these images to generate an initial 3D reconstruction of the object and the calibration target. To correct scaling and alignment errors, the system determines precise 3D measurements of the calibration target within the reconstructed coordinate system. These measurements are compared against the known dimensions of the calibration target to compute scaling and transformation factors. The system then applies these factors to the initial reconstruction, producing a scaled and accurately aligned 3D model of the object. This approach ensures that the final reconstruction is free from distortions and properly scaled, improving measurement accuracy in applications such as industrial inspection, medical imaging, or augmented reality.
19. The non-transitory computer readable medium of claim 17 , wherein the calibration target is comprised of a parameterized three-dimensional reconstruction.
A system and method for calibrating imaging devices using a parameterized three-dimensional reconstruction as a calibration target. The technology addresses the challenge of accurately calibrating imaging systems, such as cameras or sensors, to ensure precise spatial measurements and alignment in applications like augmented reality, robotics, or medical imaging. Traditional calibration methods often rely on physical targets or predefined patterns, which may be inflexible or impractical for certain environments. The invention involves generating a calibration target in the form of a parameterized three-dimensional reconstruction. This target can be dynamically adjusted based on specific calibration requirements, allowing for greater flexibility and adaptability. The system includes a processor that processes image data captured by an imaging device and compares it against the parameterized three-dimensional reconstruction to determine calibration parameters. These parameters may include intrinsic properties of the imaging device, such as focal length or lens distortion, as well as extrinsic properties like position and orientation relative to the target. The parameterized three-dimensional reconstruction can be modified in real-time, enabling the system to account for variations in the imaging environment or device characteristics. This approach improves calibration accuracy and efficiency, particularly in scenarios where physical targets are difficult to deploy or where dynamic adjustments are necessary. The system may also include a display for visualizing calibration results and a user interface for adjusting the parameterized target or calibration settings.
20. The non-transitory computer readable medium of claim 17 , wherein the first digital input includes one or more of a series of images from a singular image sensor taken from different camera positions, a video taken from different camera positions, a series of images or a video taken from different perspectives with depth information included, a 3D point cloud captured from a depth or 3D sensor, a series of images from multiple 2D sensors, a video captured from multiple 2D sensors, or a combination thereof.
This invention relates to digital input processing for generating 3D models or other outputs. The problem addressed is the need for versatile input handling to create accurate 3D representations from various sensor data sources. The invention provides a non-transitory computer-readable medium storing instructions that, when executed, process a first digital input comprising one or more of the following: a series of images from a single image sensor captured at different camera positions, a video recorded from varying camera positions, a series of images or video with depth information from different perspectives, a 3D point cloud from a depth or 3D sensor, a series of images from multiple 2D sensors, a video from multiple 2D sensors, or any combination of these inputs. The system processes these inputs to generate a 3D model or other output, enabling flexibility in capturing and reconstructing 3D environments from diverse sensor configurations. This approach allows for robust 3D reconstruction using different types of imaging data, improving adaptability in applications like augmented reality, robotics, and 3D scanning.
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September 15, 2020
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